System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization

Abstract

Systems, methods, and apparatuses for providing dynamic, prioritized spectrum utilization management. The system includes at least one monitoring sensor, at least one data analysis engine, at least one application, a semantic engine, a programmable rules and policy editor, a tip and cue server, and/or a control panel. The tip and cue server is operable utilize the environmental awareness from the data processed by the at least one data analysis engine in combination with additional information to create actionable data.

The invention claimed is: 
     
         1 . A system for dynamic, prioritized spectrum utilization management in an electromagnetic environment comprising:
 at least one data analysis engine for analyzing measured data from the electromagnetic environment to create analyzed data; and   at least one survey occupancy application;   wherein the system is operable to forecast future spectrum usage using machine learning (ML);   wherein the at least one survey occupancy application is operable to use the forecasted future spectrum usage and at least one application type to dynamically allocate at least one frequency band in the electromagnetic spectrum; and   wherein the at least one survey occupancy application is operable to determine occupancy in the at least one frequency band.   
     
     
         2 . The system of  claim 1 , further comprising at least one sensor operable to collect the measured data. 
     
     
         3 . The system of  claim 2 , wherein the at least one sensor includes at least one radio server and/or at least one software defined radio. 
     
     
         4 . The system of  claim 1 , wherein the at least one survey occupancy application is operable to preprocess at least two signals that exist in the at least one frequency band based on interference between the at least two signals. 
     
     
         5 . The system of  claim 1 , further comprising a certification and compliance application, wherein the certification and compliance application is operable to determine if at least one customer application of the at least one application type and/or at least one customer device is behaving according to at least one rule and/or at least one policy. 
     
     
         6 . The system of  claim 1 , wherein the at least one survey occupancy application is operable to schedule occupancy in a frequency band. 
     
     
         7 . The system of  claim 1 , further comprising a learning engine configured to learn the electromagnetic environment using artificial intelligence (AI), deep learning (DL), neural networks (NNs), artificial neural networks (ANNs), support vector machines (SVMs), Markov decision process (MDP), natural language processing (NLP), control theory, and/or statistical learning techniques. 
     
     
         8 . The system of  claim 1 , wherein the at least one application type includes traffic management, telemedicine, virtual reality, video streaming, social media, and/or autonomous transportation. 
     
     
         9 . A system for dynamic, prioritized spectrum utilization management in an electromagnetic environment comprising:
 at least one data analysis engine for analyzing measured data from the electromagnetic environment to create analyzed data; and   at least one survey occupancy application;   wherein the at least one data analysis engine is operable to learn the electromagnetic environment based on the analyzed data, creating a utilization mask;   wherein the system is operable to forecast future spectrum usage based on the utilization mask;   wherein the at least one survey occupancy application is operable to use at least one application type to dynamically allocate at least one frequency band in the electromagnetic spectrum; and   wherein the at least one survey occupancy application is operable to determine occupancy in the at least one frequency band.   
     
     
         10 . The system of  claim 9 , further comprising a learning engine configured to learn the electromagnetic environment using artificial intelligence (AI), deep learning (DL), neural networks (NNs), artificial neural networks (ANNs), support vector machines (SVMs), Markov decision process (MDP), natural language processing (NLP), control theory, and/or statistical learning techniques. 
     
     
         11 . The system of  claim 9 , wherein the at least one application type includes traffic management, telemedicine, virtual reality, video streaming, social media, and/or autonomous transportation. 
     
     
         12 . The system of  claim 9 , wherein the system further includes a certification and compliance application, wherein the certification and compliance application is operable to determine if at least one customer application of the at least one application type and/or at least one customer device is behaving according to at least one rule and/or at least one policy. 
     
     
         13 . The system of  claim 9 , wherein the at least one survey occupancy application is operable to preprocess at least two signals that exist in the at least one frequency band based on interference between the at least two signals. 
     
     
         14 . A method for dynamic, prioritized spectrum utilization management in an electromagnetic environment comprising:
 forecasting future spectrum usage based on historical data or measured data from the electromagnetic environment;   dynamically allocating at least one frequency band in the electromagnetic spectrum based on at least one application type and the forecasted future spectrum usage; and   determining occupancy in the at least one frequency band using a survey occupancy application.   
     
     
         15 . The method of  claim 14 , wherein the at least one application type includes traffic management, telemedicine, virtual reality, video streaming, social media, and/or autonomous transportation. 
     
     
         16 . The method of  claim 14 , further comprising the survey occupancy application preprocessing at least two signals that exist in the at least one frequency band based on interference between the at least two signals. 
     
     
         17 . The method of  claim 14 , further comprising a certification and compliance application determining if at least one customer application of the at least one application type and/or at least one customer device is behaving according to at least one rule and/or at least one policy. 
     
     
         18 . The method of  claim 14 , further comprising learning the electromagnetic environment using machine learning (ML), artificial intelligence (AI), deep learning (DL), neural networks (NNs), artificial neural networks (ANNs), support vector machines (SVMs), Markov decision process (MDP), natural language processing (NLP), control theory, and/or statistical learning techniques. 
     
     
         19 . The method of  claim 14 , further comprising generating a conditional probability set, wherein the conditional probability set indicates an optimal outcome for a scenario. 
     
     
         20 . The method of  claim 14 , further comprising determining an impact of interference on customer goals and/or customer operations and allocating the at least one frequency band in the electromagnetic spectrum based on the determined impact of the interference.